Minimum Recall-Based Loss Function for Imbalanced Time Series Classification-Reference-Cited by-同舟云学术

Minimum Recall-Based Loss Function for Imbalanced Time Series Classification

Published:2023-10-01 Issue:10 Volume:35 Page:10024-10034
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Ircio Josu¹^ORCID,Lojo Aizea¹^ORCID,Mori Usue²^ORCID,Malinowski Simon³^ORCID,Lozano Jose A.²^ORCID

Affiliation:

1. Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), Arrasate-Mondragón, Spain

2. Department of Computer-Science and Artificial Intelligence, Intelligent Systems Group, University of the Basque Country UPV/EHU, San Sebastian, Spain

3. IRISA UMR 6074, Univ Rennes, Rennes, France

Funder

Eusko Jaurlaritza

Ministry of Science and Innovation: BCAM Severo Ochoa accreditation

Elkartek program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/10251471/10106021.pdf?arnumber=10106021

Reference44 articles.

1. SMOTE: Synthetic Minority Over-sampling Technique

2. The UEA & UCR time series classification repository;bagnall,0

3. An Effective Method for Imbalanced Time Series Classification: Hybrid Sampling

4. On the properties of the softmax function with application in game theory and reinforcement learning;gao,2017

5. A Parsimonious Mixture of Gaussian Trees Model for Oversampling in Imbalanced and Multimodal Time-Series Classification

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